arXiv Machine Learning By Hongjian Zhou, Xianfan Nie, Sean Wu, Tarun Patel, Jinge Wu, Andrew Liu, Adam Wei Tsen, David A. Clifton

The AI Theorist reveals excitonic structure in $\alpha$-RuCl$_3$

Read the original on arXiv Machine Learning →

The paper introduces AI Theorist, a system of AI agents that autonomously discovers physical models by generating hypotheses, performing first‑principles calculations, and refining them based on evidence. Applied to the quantum material α‑RuCl₃, the system interprets optical and photocurrent data, revealing distinct excitonic states with different optical selection rules and spatial distributions. This marks the first demonstration of an AI system autonomously developing a physical model to explain previously unpublished experimental observations in a quantum material using first‑principles and many‑body calculations.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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By Zach Winn | MIT News